Doubly effects of information sharing on interdependent network reciprocity
Understanding large-scale cooperation among unrelated individuals is one of the greatest challenges of the 21st century. Since human cooperation evolves on social networks, the theoretical framework of multilayer networks is perfectly suited for studying this fascinating aspect of our biology. To th...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2018-01-01
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| Series: | New Journal of Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1367-2630/aad140 |
| _version_ | 1797750616149196800 |
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| author | Chengyi Xia Xiaopeng Li Zhen Wang Matjaž Perc |
| author_facet | Chengyi Xia Xiaopeng Li Zhen Wang Matjaž Perc |
| author_sort | Chengyi Xia |
| collection | DOAJ |
| description | Understanding large-scale cooperation among unrelated individuals is one of the greatest challenges of the 21st century. Since human cooperation evolves on social networks, the theoretical framework of multilayer networks is perfectly suited for studying this fascinating aspect of our biology. To that effect, we here study the cooperation in evolutionary games on interdependent networks, such that players in one network layer play the snowdrift game (SDG), and the prisoner’s dilemma game (PDG) in the other layer. Importantly, players are able to share information across two layers, which in turn affects their strategy choices. Monte Carlo simulations reveal that the transfer of information about the strategy of the corresponding player in the other network layer alone is enough to significantly promote the overall level of cooperation. However, while the cooperation is markedly enhanced in the layer where the PDG is played, the opposite is true, albeit to a lesser extent, for the layer where the SDG is played. The net increase in cooperation is thus due to a doubly effect of information sharing. We show further that the more complete the information transfer, the more the overall level of cooperation is promoted, and that this holds as long as the information channels between the player do not vary over time. We discuss potential implications of these findings for future human experiments concerning the cooperation on multilayer networks. |
| first_indexed | 2024-03-12T16:36:21Z |
| format | Article |
| id | doaj.art-5187eac02979481ca736c8715b32f004 |
| institution | Directory Open Access Journal |
| issn | 1367-2630 |
| language | English |
| last_indexed | 2024-03-12T16:36:21Z |
| publishDate | 2018-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj.art-5187eac02979481ca736c8715b32f0042023-08-08T14:51:46ZengIOP PublishingNew Journal of Physics1367-26302018-01-0120707500510.1088/1367-2630/aad140Doubly effects of information sharing on interdependent network reciprocityChengyi Xia0Xiaopeng Li1Zhen Wang2Matjaž Perc3Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology , Tianjin 300384, People's Republic of China; Key Laboratory of Computer Vision and System (Ministry of Education), Tianjin University of Technology , Tianjin 300384, People's Republic of ChinaTianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology , Tianjin 300384, People's Republic of China; Key Laboratory of Computer Vision and System (Ministry of Education), Tianjin University of Technology , Tianjin 300384, People's Republic of ChinaSchool of Mechanical Engineering and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University , Xi’an 710072, People's Republic of ChinaFaculty of Natural Sciences and Mathematics, University of Maribor , Koroška cesta 160, SI-2000 Maribor, Slovenia; CAMTP—Center for Applied Mathematics and Theoretical Physics, University of Maribor , Mladinska 3, SI-2000 Maribor, Slovenia; School of Electronic and Information Engineering, Beihang University , Beijing 100191, People's Republic of ChinaUnderstanding large-scale cooperation among unrelated individuals is one of the greatest challenges of the 21st century. Since human cooperation evolves on social networks, the theoretical framework of multilayer networks is perfectly suited for studying this fascinating aspect of our biology. To that effect, we here study the cooperation in evolutionary games on interdependent networks, such that players in one network layer play the snowdrift game (SDG), and the prisoner’s dilemma game (PDG) in the other layer. Importantly, players are able to share information across two layers, which in turn affects their strategy choices. Monte Carlo simulations reveal that the transfer of information about the strategy of the corresponding player in the other network layer alone is enough to significantly promote the overall level of cooperation. However, while the cooperation is markedly enhanced in the layer where the PDG is played, the opposite is true, albeit to a lesser extent, for the layer where the SDG is played. The net increase in cooperation is thus due to a doubly effect of information sharing. We show further that the more complete the information transfer, the more the overall level of cooperation is promoted, and that this holds as long as the information channels between the player do not vary over time. We discuss potential implications of these findings for future human experiments concerning the cooperation on multilayer networks.https://doi.org/10.1088/1367-2630/aad140cooperationevolutionary gamesMonte Carlo methodmultilayer networkinterdependent network reciprocity |
| spellingShingle | Chengyi Xia Xiaopeng Li Zhen Wang Matjaž Perc Doubly effects of information sharing on interdependent network reciprocity New Journal of Physics cooperation evolutionary games Monte Carlo method multilayer network interdependent network reciprocity |
| title | Doubly effects of information sharing on interdependent network reciprocity |
| title_full | Doubly effects of information sharing on interdependent network reciprocity |
| title_fullStr | Doubly effects of information sharing on interdependent network reciprocity |
| title_full_unstemmed | Doubly effects of information sharing on interdependent network reciprocity |
| title_short | Doubly effects of information sharing on interdependent network reciprocity |
| title_sort | doubly effects of information sharing on interdependent network reciprocity |
| topic | cooperation evolutionary games Monte Carlo method multilayer network interdependent network reciprocity |
| url | https://doi.org/10.1088/1367-2630/aad140 |
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